jms-data-analysis
Use when the execution and credibility of the analysis is the bottleneck for a Journal of Management Studies (JMS) manuscript — regression/SEM and robustness for quantitative work, OR coding, abduction, and trustworthiness for qualitative work. Runs and defends the analysis; it does not design the study (jms-methods) or build exhibits (jms-tables-figures).
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jms-data-analysis --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Data Analysis (jms-data-analysis) ## When to trigger - Estimates are in but reviewers question endogeneity, robustness, or the indirect-effect claim - A qualitative analysis reaches findings but the path from data to constructs is not auditable - Effects hinge on a single specification with no robustness - A mediation/moderation result is reported without the analysis JMS expects - A reviewer says "the analysis does not support the claim" or "I can't see how you got here" ## The JMS analysis bar — two idioms, one standard JMS judges analysis by whether it **credibly supports the theoretical claim**, in whichever idiom the study uses. Quantitative work is held to identification and robustness standards; qualitative work is held to **trustworthiness and transparency** standards. Use the path that matches your design; do not import quant criteria (p-values, effect sizes) to judge a qualitative paper, or qualitative looseness into a quantitative one. ## Quantitative path - **Specification & estimator**: match the estimator to the data structure (OLS/GLM, fixed effects for panels, SEM for latent constructs and full mediation models, multilevel models for nested data). State why. - **M
- When to trigger
- The JMS analysis bar — two idioms, one standard
- Quantitative path
- Qualitative path
- Execution bridge (StatsPAI / Stata MCP)
- Checklist
- Anti-patterns
- Output format
What does the jms-data-analysis skill do?
Use when the execution and credibility of the analysis is the bottleneck for a Journal of Management Studies (JMS) manuscript — regression/SEM and robustness for quantitative work, OR coding, abduction, and trustworthiness for qualitative work. Runs and defends the analysis; it does not design the study (jms-methods) or build exhibits (jms-tables-figures).
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jms-data-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.